delphi 1e22 9 7Bparams 160Btokens base wc386k lr1e5 sft

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released June 20264K context≈ 3,072 words

A compact open-weight base model from LAION, trained on 160 billion tokens with a relatively small learning rate, then fine-tuned via supervised fine-tuning. At 7 billion parameters, it sits in a familiar size range — capable enough for many language tasks but constrained by its 4096-token context window. The specific training corpus (wc386k) and SFT process shape its behavior, though detailed capability benchmarks aren't widely documented.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Creative Writing

Moderate

Instruction Following

delphi 1e22 9 7Bparams 160Btokens base wc386k lr1e5 sft

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released June 20264K context≈ 3,072 words

A compact open-weight base model from LAION, trained on 160 billion tokens with a relatively small learning rate, then fine-tuned via supervised fine-tuning. At 7 billion parameters, it sits in a familiar size range — capable enough for many language tasks but constrained by its 4096-token context window. The specific training corpus (wc386k) and SFT process shape its behavior, though detailed capability benchmarks aren't widely documented.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Creative Writing

Moderate

Instruction Following

Glossary

Base ModelA pretrained model that completes text patterns but hasn't been trained to follow instructions, serving as a starting point for customization through fine-tuning.Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.CorpusA collection of documents or text used as the knowledge base for retrieval in RAG systems.Fine-TunedA pre-trained model further trained on a smaller, task-specific dataset to improve performance on that task.Fine-TuningThe process of further training a pre-trained model on new data to adapt it for specific tasks or domains.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.Supervised Fine-tuningTraining a model on labeled examples to adapt it for a specific task or domain.Supervised Fine-tuningAdapting a pre-trained model using labeled examples where the correct outputs are known.TokenA small unit of text (a word, subword, or punctuation mark) that a language model breaks input into for processing.TokensThe basic units of text that a language model processes, typically representing words or word fragments.

Capabilities

Capabilities

Use Case Fit

Glossary